Protein-based biologics ? therapeutics whose active ingredient is a protein and most commonly a monoclonal antibody (mAb) ? make up a $200 billion/year market that is expected to double in size by 2025. A critical component in the safety and efficacy of biologics is the need to maintain the active protein during long-term storage and subsequent injection/infusion. The selection of excipients and buffers toward this end is termed ?formulation.? Proper formulation of a protein-based drug is essential to stabilize the active protein from unfolding and to block sites on the folded protein that would otherwise pose an aggregation risk due to undesirable protein-protein interactions (PPI). Importantly, formulation can be done without altering the sequence of (i.e. re-engineering) the protein, and is thus an independent tool for bringing a biologic therapeutic to market. Current approaches to choosing an optimized formulation are either low-throughput experiments or crude computational methods that do not take into account the molecular details of excipient-protein interactions. To understand at the level of atomic interactions how excipient/buffer combinations modulate protein stability and aggregation requires a new approach, which if successfully developed can provide mechanistic insight for rational formulation. The established Site Identification by Ligand Competitive Saturation (SILCS) computational platform technology maps, at atomic resolution, the affinity pattern of the complete 3D surface of a protein for a wide diversity of chemical functional groups. The functional group affinity pattern can be used to determine excipients that can bind to and stabilize the active, folded conformation of a protein and bind to and block those regions of the protein that may participate in PPI, thereby inhibiting aggregation. The broad goal of the proposal is to develop comprehensive and industry-ready workflows for screening excipients that could stabilize the protein structure and prevent aggregation.. New computational tools and a graphical user interface will be developed to manage and apply the extensive information generated by SILCS excipient screening and PPI analysis. The tools will predict excipient/buffer binding locations and potential regions that can participate in PPI across the complete protein surface. This information will then be applied to predict excipients that will stabilize the folded, biologically active state of the protein and block PPI thereby slowing aggregation while simultaneously considering the impact of buffers. The proposed approaches will be thoroughly validated in collaboration with industrial and government partners against established experimental methods on well-characterized systems. Upon successful completion of the project new offerings will be added to the existing SILCS software suite that will minimize the time and costs requirements for the formulation of biologics as well as lead to improved formulations thereby improving clinical outcomes. These capabilities will be implemented in the context of industry-ready workflows for direct sale to pharmaceutical companies and for use in contract research for the optimized formulation of biologics.